Analysis Of Non-Line-Of-Sight (Nlos) Bias Correction Techniques For Wireless Indoor Positioning Systems

Student thesis: Master's Thesis


This dissertation proposes a novel solution for improving the accuracy of wireless indoor-positioning systems(IPS)in general and wireless local area networks(WLANs)in particular.The market potential for indoor-positioning based services in several domains including retail,health,and autonomous systems has motivated research to design accu-rate,cost-effective solutions. Among the potential technologies for deployment,WLAN can enable rapid and cost-effective and deployment given its widely available infrastruc-ture. Wireless positioning techniques calculate the location of mobilenodes(MN)using range signal measurements; e.g. Time-of-Flight (TOF) and Received Signal Strength (RSS),which indicate the distance relative to reference access points (APs).In indoor environments,range measurements are severely biased due to multi path propagation,the low-probability of line of sight given the obstacle-rich environment. In this dissertation,we propose an algorithm for correcting ranging measurements through recursive estimation and removal of the bias.Unlike existing bias-correction solutions,the proposed algorithm is a non-parametric estimator that does not require a priori information about the implementation environment,leading to a cost-effective and accurate deployment. Simulation results indicate that the proposed algorithm yields higher positioning accuracy incomparison with the state of the art.
Date of AwardMay 2018
Original languageAmerican English
SupervisorNawaf Al Moosa (Supervisor)


  • Indoor Positioning
  • Bias Correction
  • NLOS
  • Controller
  • Adaptive Windowing.

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